Artificial Intelligence has found useful applications in every possible domain, and manufacturing is also on that list. Automation in manufacturing makes it faster, cheaper, and more accurate. A large part of the manufacturing process involves inspection of various objects to ensure proper build. Looking for errors traditionally used to be a manual process. A worker had to look at individual objects and check for any missing elements in them. Such analysis was slow and time-consuming. However, no compromise could be made in this process as quality control is an important parameter in manufacturing and has severe consequences if it is not followed per the book. AI has been an integral part of improving this process.
What is Machine Vision?
Machine vision is the ability of a machine to capture images and analyze them so that it can respond to inputs in a certain way. Machine vision involves the usage of high-quality cameras that capture images or videos of the object concerned. The images are then converted to digital data which is fed into a computer. Such data is processed by computer algorithms like deep learning models to “train” the machine vision system to recognize such objects, and even find any abnormalities in those objects.
Material Handling in Manufacturing
Material handling is the movement, storage, protection, and control of materials throughout the process of manufacturing. Material handling usually is done with a wide array of systems, some manual and some semi-automated. There has been a shift in material handling towards more automatic procedures like automated storage and retrieval systems, automatic guided vehicles, automatic identification, and data collection, etc. To design a good material handling system, the common points to consider are –
- Planning – The definition of needs, objectives, and functional specifications discussed by the entire team end in the formulation of a solid plan.
- Standardization – A standardized model will allow the handling to be seamless and perform a wide range of tasks in various operating conditions.
- Work – The processes should be simplified by eliminating unnecessary movement that reduces productivity.
- System – The movement of materials should be coordinated from the start to the end. The system should be able to identify and track an item from storage to production to delivery.
- Automation – To improve the overall efficiency of material handling, automated technologies should be used as far as possible.
Machine vision technology covers all these points in material handling and makes for a system that requires the least human intervention to perform tasks.
Applications of Machine Vision in Manufacturing
- Predictive maintenance –
The manufacturing industry functions with the help of powerful and heavy-duty machinery which bear the brunt of the entire process. Any fault in these machines will cause operations to shut down and the company to suffer losses. Using machine vision, pictures of every piece of equipment can be captured and examined for errors before shutdown can occur.
- Product inspection and quality control –
Manual inspection of components is boring, repetitive, and time-intensive. It is also more prone to errors. Using machine vision systems, manufacturing companies can detect faults or irregularities in the components more easily and quickly with improved accuracy.
- Reading barcodes –
Barcode scanners are extremely essential in the manufacturing industry. Machine vision uses Optical Character Recognition (OCR) to read barcodes. This helps the system to track a component all the time. It ensures that all components follow the right path along the assembly line, or keep tabs on the packages that are shipped.
- Safe work environment –
Even with safety protocols in place, accidents can always happen when handling heavy-duty equipment. Replacing automation and machine vision in possibly risky environments can ensure the safety of workers. The worker can see through the eyes of the machine vision system and make decisions if necessary.
Also, Read 3 Uncommon Applications of Machine Vision
How can AI ensure repeatability?
AI in the machine vision system uses deep learning technology to train itself. When pictures are fed into the computer, these algorithms identify similarities in the images of the same type of object, and with enough data, they can successfully identify an object independently. The accuracy of deep learning models keeps increasing over time as they keep learning and improving whenever they identify an object. The more the machine vision system works, the better it becomes at a certain task. The AI has no difficulty replicating the same result again and again. It does that with increased accuracy and speed over time.
Can MV handle scenarios where dimensions keep changing?
As MV is self-learning, it can apply various techniques to handle cases where dimensional and orientation differences are present. For instance, MV uses a coordinate measurement machine to handle orientation changes. It just needs a reference point or “zero” point based on which it maps an object automatically.
For dimension differences, MV uses a ratio-based approach to understand the changes in the object geometry and hence identify the object accurately. Usually, when the machine vision system deals with a complex part, it uses superimposed videos to observe the image in additional axes. This helps the model to navigate complex geometry, which is a common challenge in manufacturing industries.
Thus, Machine Vision has found its use in the manufacturing industry at all stages of a product development process. From storage to production, and from transport to delivery, machine vision contributes to the supply chain in important ways. Machine vision has remarkable learning capabilities and a wide range of tasks it can perform.
This makes it ideal for the manufacturing industry where repetitive work with configurable changes happens periodically. Machine vision can identify objects, track them and find defects in them. Coupled with robots, machine vision can work as an independent entity, saving time, money, and effort of the manufacturing company. Machine vision is a developing field, and it will have more applications in this industry as time passes.